1、es常用的聚合查询有三种
桶聚合
指标聚合
管道聚合
首先我们创建一个product的索引，并插入数据
PUT /product
{"mappings": {"properties": {"category": { "type": "keyword" },"price": { "type": "float" },"timestamp": { "type": "date" }}}
}POST /product/_doc/1
{"category": "iphone","price": 1200,"timestamp": "2024-04-01"
}POST /product/_doc/2
{"category": "Electronics","price": 800,"timestamp": "2024-04-10"
}POST /product/_doc/3
{"category": "Clothing","price": 50,"timestamp": "2024-04-10"
}POST /product/_doc/4
{"category": "Clothing","price": 30,"timestamp": "2024-04-15"
}POST /product/_doc/5
{"category": "Electronics","price": 1500,"timestamp": "2024-05-21"
}
2、桶聚合：常用的桶聚合如下
Terms聚合 - 类似SQL的group by，根据字段唯一值分组；
Histogram聚合 - 根据数值间隔分组，例如: 价格按100间隔分组，0、100、200、300等等；
Date histogram聚合 - 根据时间间隔分组，例如：按月、按天、按小时分组；
Range聚合 - 按数值范围分组，例如: 0-150一组，150-200一组，200-500一组；
比如：我想根据category字段唯一值来分组
GET /product/_search?size=0
{"aggs": {"shop": { //聚合查询的名字，随便取个名字"terms": { //聚合类型为: terms"field": "category" //要聚合分组的字段}}}
}
以上好比sql为
select category, count(*) from product group by category
结果为：
{"took" : 1,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 5,"relation" : "eq"},"max_score" : null,"hits" : [ ]},"aggregations" : {"shop" : {"doc_count_error_upper_bound" : 0,"sum_other_doc_count" : 0,"buckets" : [{"key" : "Clothing", //key是category的各种情况"doc_count" : 2 //是每种category的次数},{"key" : "Electronics","doc_count" : 2},{"key" : "iphone","doc_count" : 1}]}}
}以上这种写法经常用到下拉框列表的聚合分组查询。
2、按照产品类别进行分组，并计算每个类别下的平均价格
GET /product/_search
{"size": 0,"aggs": {"category_buckets": {"terms": {"field": "category"},"aggs": {"avg_price": {"avg": {"field": "price"}}}}}
}
结果如下：
{"took" : 5,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 5,"relation" : "eq"},"max_score" : null,"hits" : [ ]},"aggregations" : {"category_buckets" : {"doc_count_error_upper_bound" : 0,"sum_other_doc_count" : 0,"buckets" : [{"key" : "Clothing","doc_count" : 2,"avg_price" : {"value" : 40.0}},{"key" : "Electronics","doc_count" : 2,"avg_price" : {"value" : 1150.0}},{"key" : "iphone","doc_count" : 1,"avg_price" : {"value" : 1200.0}}]}}
}3、指标聚合：指标聚合对文档中的数值字段执行统计操作，如求和、平均值、最大值、最小值等
比如：计算所有产品的平均价格。
{"took" : 0,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 5,"relation" : "eq"},"max_score" : null,"hits" : [ ]},"aggregations" : {"avg_price" : {"value" : 716.0}}
}比如：计算所有商品的最大价格
GET /product/_search
{"size": 0,"aggs": {"avg_price": {"max": {"field": "price"}}}
}
4、写一个复杂的聚合查询，并配合query查询
比如我想筛出 category = Electronics 和Clothing 的商品，然后在这基础上对category分组，求分组后category的平均值及合计两个字段
GET /product/_search
{"size": 0, //size=0代表不需要返回query查询结果，仅仅返回aggs统计结果"query": { //query查询category=Electronics 和Clothing的数据"terms": {"category": ["Electronics","Clothing"]}},"aggs": { //开始对category字段聚合分组"product_category": { //聚合名称"terms": {"field": "category"},"aggs": { //聚合名称 "avg_price": {"avg": { // 指标聚合类型为avg"field": "price"}},"sum_price":{ //聚合名称"sum": { //指标聚合类型为sum"field": "price"}}}}}
}
结果如下：
{"took" : 27,"timed_out" : false,"_shards" : {"total" : 1,"successful" : 1,"skipped" : 0,"failed" : 0},"hits" : {"total" : {"value" : 4,"relation" : "eq"},"max_score" : null,"hits" : [ ]},"aggregations" : {"product_category" : {"doc_count_error_upper_bound" : 0,"sum_other_doc_count" : 0,"buckets" : [{"key" : "Clothing","doc_count" : 2,"avg_price" : {"value" : 40.0},"sum_price" : {"value" : 80.0}},{"key" : "Electronics","doc_count" : 2,"avg_price" : {"value" : 1150.0},"sum_price" : {"value" : 2300.0}}]}}
}
后续更新管道聚合
)
